requirements: update matplotlib requirement from <3.7.6 to <3.9.4

[dependabot]

Updates the requirements on matplotlib to permit the latest version.

Release notes

Sourced from matplotlib's releases.

REL: 3.9.3

This is the third bugfix release of the 3.9.x series.

This release contains several bug-fixes and adjustments:

• Fix axline with extremely small slopes
• Fix axline with non-linear axis scales
• Fix minimumSizeHint with Qt backend
• Fix config directory usage when it's behind a symlink
• Fix draggable legend when blitting is enabled
• Fix high CPU utilization in the macosx backend
• Fix multiple hatch edgecolors passed to contourf
• Improve compatibility with pytest 8.2.0

Commits

• 3ac0aea REL: 3.9.3
• 3f7adbd Merge branch 'v3.9.2-doc' into v3.9.x
• 4ca8d68 DOC: Create release notes for 3.9.3
• 0cabfe2 Merge pull request #29195 from meeseeksmachine/auto-backport-of-pr-29191-on-v...
• 562d458 Backport PR #29191: ci: Simplify 3.13t test setup
• 0586854 Merge pull request #29176 from meeseeksmachine/auto-backport-of-pr-29148-on-v...
• 84f2ae2 Merge pull request #29178 from meeseeksmachine/auto-backport-of-pr-29163-on-v...
• dd57772 Backport PR #29163: ci: Remove outdated pkg-config package on macOS
• c4bfd54 Backport PR #29148: Don't fail on equal-but-differently-named cmaps in qt fig...
• d71ff49 Backport PR #29153: Bump codecov/codecov-action from 4 to 5 in the actions gr...
• Additional commits viewable in compare view

You can trigger a rebase of this PR by commenting @dependabot rebase.

---

Dependabot commands and options

You can trigger Dependabot actions by commenting on this PR:

• @dependabot rebase will rebase this PR
• @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
• @dependabot merge will merge this PR after your CI passes on it
• @dependabot squash and merge will squash and merge this PR after your CI passes on it
• @dependabot cancel merge will cancel a previously requested merge and block automerging
• @dependabot reopen will reopen this PR if it is closed
• @dependabot close will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually
• @dependabot show <dependency name> ignore conditions will show all of the ignore conditions of the specified dependency
• @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
• @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
• @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)

[github-actions]

This PR causes the following changes to the html docs (ubuntu-latest-3.11):

diff -r docs-base/AutodiffComposition.html docs-head/AutodiffComposition.html
288,296c288,291
< to <code class="xref any docutils literal notranslate"><span class="pre">False</span></code>.</p>
< <blockquote>
< <div><p>Trainable biases <em>can</em> be specified explicitly in an AutodiffComposition by including a <a class="reference internal" href="ProcessingMechanism.html"><span class="doc">ProcessingMechanism</span></a>
< that projects to the relevant Mechanism (i.e., implementing that layer of the network to receive the biases)
< using a <a class="reference internal" href="MappingProjection.html"><span class="doc">MappingProjection</span></a> with a <a class="reference internal" href="MappingProjection.html#psyneulink.core.components.projections.pathway.mappingprojection.MappingProjection.matrix" title="psyneulink.core.components.projections.pathway.mappingprojection.MappingProjection.matrix"><code class="xref any py py-attr docutils literal notranslate"><span class="pre">matrix</span></code></a> parameter that implements a diagnoal
< matrix with values corresponding to the initial value of the biases, and setting the <a class="reference internal" href="InputPort.html#psyneulink.core.components.ports.inputport.InputPort.default_input" title="psyneulink.core.components.ports.inputport.InputPort.default_input"><code class="xref any py py-attr docutils literal notranslate"><span class="pre">default_input</span></code></a> Parameter of one of the ProcessingMechanism’s <a class="reference internal" href="Mechanism.html#psyneulink.core.components.mechanisms.mechanism.Mechanism_Base.input_ports" title="psyneulink.core.components.mechanisms.mechanism.Mechanism_Base.input_ports"><code class="xref any py py-attr docutils literal notranslate"><span class="pre">input_ports</span></code></a> to <em>DEFAULT_VARIABLE</em>, and its <code class="xref any docutils literal notranslate"><span class="pre">default_variable</span></code>
< equal to 1. ProcessingMechanisms configured in this way are assigned <a class="reference internal" href="Composition.html#psyneulink.core.compositions.composition.NodeRole" title="psyneulink.core.compositions.composition.NodeRole"><code class="xref any py py-class docutils literal notranslate"><span class="pre">NodeRole</span></code></a> <a class="reference internal" href="Composition.html#psyneulink.core.compositions.composition.NodeRole.BIAS" title="psyneulink.core.compositions.composition.NodeRole.BIAS"><code class="xref any py py-attr docutils literal notranslate"><span class="pre">BIAS</span></code></a>, and the MappingProjection
< is subject to learning.</p>
< </div></blockquote>
---
> to <code class="xref any docutils literal notranslate"><span class="pre">False</span></code>. Trainable biases <em>can</em> be specified explicitly in an AutodiffComposition by including a
> TransferMechanism that projects to the relevant Mechanism (i.e., implementing that layer of the network to
> receive the biases) using a <a class="reference internal" href="MappingProjection.html"><span class="doc">MappingProjection</span></a> with a <a class="reference internal" href="MappingProjection.html#psyneulink.core.components.projections.pathway.mappingprojection.MappingProjection.matrix" title="psyneulink.core.components.projections.pathway.mappingprojection.MappingProjection.matrix"><code class="xref any py py-attr docutils literal notranslate"><span class="pre">matrix</span></code></a> parameter that
> implements a diagnoal matrix with values corresponding to the initial value of the biases.</p>
diff -r docs-base/Composition.html docs-head/Composition.html
5706c5706
< input that is constant across executions). Such a node can also be assigned as an <a class="reference internal" href="#psyneulink.core.compositions.composition.NodeRole.INPUT" title="psyneulink.core.compositions.composition.NodeRole.INPUT"><code class="xref any py py-attr docutils literal notranslate"><span class="pre">INPUT</span></code></a> and/or <a class="reference internal" href="#psyneulink.core.compositions.composition.NodeRole.ORIGIN" title="psyneulink.core.compositions.composition.NodeRole.ORIGIN"><code class="xref any py py-attr docutils literal notranslate"><span class="pre">ORIGIN</span></code></a>,
---
> input that is constant across executions).  Such a node can also be assigned as an <a class="reference internal" href="#psyneulink.core.compositions.composition.NodeRole.INPUT" title="psyneulink.core.compositions.composition.NodeRole.INPUT"><code class="xref any py py-attr docutils literal notranslate"><span class="pre">INPUT</span></code></a> and/or <a class="reference internal" href="#psyneulink.core.compositions.composition.NodeRole.ORIGIN" title="psyneulink.core.compositions.composition.NodeRole.ORIGIN"><code class="xref any py py-attr docutils literal notranslate"><span class="pre">ORIGIN</span></code></a>,
diff -r docs-base/ControlMechanism.html docs-head/ControlMechanism.html
386c386
< its corresponding <a class="reference internal" href="ObjectiveMechanism.html#psyneulink.core.components.mechanisms.processing.objectivemechanism.ObjectiveMechanism.input_ports" title="psyneulink.core.components.mechanisms.processing.objectivemechanism.ObjectiveMechanism.input_ports"><code class="xref any py py-attr docutils literal notranslate"><span class="pre">input_ports</span></code></a>.  When the Composition is run, the <a class="reference internal" href="OutputPort.html#psyneulink.core.components.ports.outputport.OutputPort.value" title="psyneulink.core.components.ports.outputport.OutputPort.value"><code class="xref any py py-attr docutils literal notranslate"><span class="pre">value</span></code></a>(s) of the OutputPort(s) monitored are evaluated using the <a class="reference internal" href="LCControlMechanism.html#psyneulink.library.components.mechanisms.modulatory.control.agt.lccontrolmechanism.LCControlMechanism.objective_mechanism" title="psyneulink.library.components.mechanisms.modulatory.control.agt.lccontrolmechanism.LCControlMechanism.objective_mechanism"><code class="xref any py py-attr docutils literal notranslate"><span class="pre">objective_mechanism</span></code></a>'s <a class="reference internal" href="ObjectiveMechanism.html#psyneulink.core.components.mechanisms.processing.objectivemechanism.ObjectiveMechanism.function" title="psyneulink.core.components.mechanisms.processing.objectivemechanism.ObjectiveMechanism.function"><code class="xref any py py-attr docutils literal notranslate"><span class="pre">function</span></code></a>, and the result is assigned to its <em>OUTCOME</em> <a class="reference internal" href="ObjectiveMechanism.html#objectivemechanism-output"><span class="std std-ref">output_port</span></a>.  That <code class="xref any docutils literal notranslate"><span class="pre">value</span></code> is then passed to the ControlMechanism’s
---
> its corresponding <a class="reference internal" href="ObjectiveMechanism.html#psyneulink.core.components.mechanisms.processing.objectivemechanism.ObjectiveMechanism.input_ports" title="psyneulink.core.components.mechanisms.processing.objectivemechanism.ObjectiveMechanism.input_ports"><code class="xref any py py-attr docutils literal notranslate"><span class="pre">input_ports</span></code></a>.  When the Composition is run, the <a class="reference internal" href="OutputPort.html#psyneulink.core.components.ports.outputport.OutputPort.value" title="psyneulink.core.components.ports.outputport.OutputPort.value"><code class="xref any py py-attr docutils literal notranslate"><span class="pre">value</span></code></a>(s) of the OutputPort(s) monitored are evaluated using the <a class="reference internal" href="#psyneulink.core.components.mechanisms.modulatory.control.controlmechanism.ControlMechanism.objective_mechanism" title="psyneulink.core.components.mechanisms.modulatory.control.controlmechanism.ControlMechanism.objective_mechanism"><code class="xref any py py-attr docutils literal notranslate"><span class="pre">objective_mechanism</span></code></a>'s <a class="reference internal" href="ObjectiveMechanism.html#psyneulink.core.components.mechanisms.processing.objectivemechanism.ObjectiveMechanism.function" title="psyneulink.core.components.mechanisms.processing.objectivemechanism.ObjectiveMechanism.function"><code class="xref any py py-attr docutils literal notranslate"><span class="pre">function</span></code></a>, and the result is assigned to its <em>OUTCOME</em> <a class="reference internal" href="ObjectiveMechanism.html#objectivemechanism-output"><span class="std std-ref">output_port</span></a>.  That <code class="xref any docutils literal notranslate"><span class="pre">value</span></code> is then passed to the ControlMechanism’s
diff -r docs-base/EMComposition.html docs-head/EMComposition.html
231,232d230
< <li><p><a class="reference internal" href="#emcomposition-memory-specification"><span class="std std-ref">Memory</span></a></p></li>
< <li><p><a class="reference internal" href="#emcomposition-memory-capacity"><span class="std std-ref">Capacity</span></a></p></li>
233a232
> <li><p><a class="reference internal" href="#emcomposition-memory-capacity"><span class="std std-ref">Capacity</span></a></p></li>
243c242
< <li><p><a class="reference internal" href="#emcomposition-memory-structure"><span class="std std-ref">Memory</span></a></p></li>
---
> <li><p><a class="reference internal" href="#emcomposition-memory"><span class="std std-ref">Memory</span></a></p></li>
252c251
< <li><p><a class="reference internal" href="#emcomposition-training"><span class="std std-ref">Learning</span></a></p></li>
---
> <li><p><a class="reference internal" href="#emcomposition-learning"><span class="std std-ref">Learning</span></a></p></li>
271c270
< <p>The EMComposition implements a configurable, content-addressable form of episodic (or external) memory. It emulates
---
> <p>The EMComposition implements a configurable, content-addressable form of episodic, or eternal memory, that emulates
273,291c272,280
< in the form of an <a class="reference internal" href="AutodiffComposition.html"><span class="doc">AutodiffComposition</span></a>. This allows it to backpropagate error signals based retrieved values to
< it inputs, and learn how to differentially weight cues (queries) used for retrieval. It also adds the capability for
< <a class="reference internal" href="#psyneulink.library.compositions.emcomposition.EMComposition.memory_decay_rate" title="psyneulink.library.compositions.emcomposition.EMComposition.memory_decay_rate"><code class="xref any py py-attr docutils literal notranslate"><span class="pre">memory_decay</span></code></a>. In these respects, it implements a variant of a <a class="reference external" href="https://en.wikipedia.org/wiki/Modern_Hopfield_network">Modern Hopfield
< Network</a>, as well as some of the features of a <a class="reference external" href="https://en.wikipedia.org/wiki/Transformer_(deep_learning_architecture)">Transformer</a></p>
< <p>The <a class="reference internal" href="#psyneulink.library.compositions.emcomposition.EMComposition.memory" title="psyneulink.library.compositions.emcomposition.EMComposition.memory"><code class="xref any py py-attr docutils literal notranslate"><span class="pre">memory</span></code></a> of an EMComposition is configured using two arguments of its constructor:
< the <strong>memory_template</strong> argument, that defines the overall structure of its <a class="reference internal" href="#psyneulink.library.compositions.emcomposition.EMComposition.memory" title="psyneulink.library.compositions.emcomposition.EMComposition.memory"><code class="xref any py py-attr docutils literal notranslate"><span class="pre">memory</span></code></a> (the
< number of fields in each entry, the length of each field, and the number of entries); and <strong>fields</strong> argument, that
< defines which fields are used as cues for retrieval (i.e., as “keys”), including whether and how they are weighted in
< the match process used for retrieval, which fields are treated as “values” that are stored retrieved but not used by
< the match process, and which are involved in learning. The inputs to an EMComposition, corresponding to its keys and
< values, are assigned to each of its <a class="reference internal" href="Composition.html#psyneulink.core.compositions.composition.NodeRole.INPUT" title="psyneulink.core.compositions.composition.NodeRole.INPUT"><code class="xref any py py-attr docutils literal notranslate"><span class="pre">INPUT</span></code></a> <a class="reference internal" href="Composition.html#composition-nodes"><span class="std std-ref">Nodes</span></a>: inputs to be matched to keys
< (i.e., used as “queries”) are assigned to its <a class="reference internal" href="#psyneulink.library.compositions.emcomposition.EMComposition.query_input_nodes" title="psyneulink.library.compositions.emcomposition.EMComposition.query_input_nodes"><code class="xref any py py-attr docutils literal notranslate"><span class="pre">query_input_nodes</span></code></a>; and the remaining
< inputs assigned to it <a class="reference internal" href="#psyneulink.library.compositions.emcomposition.EMComposition.value_input_nodes" title="psyneulink.library.compositions.emcomposition.EMComposition.value_input_nodes"><code class="xref any py py-attr docutils literal notranslate"><span class="pre">value_input_nodes</span></code></a>. When the EMComposition is executed, the
< retrieved values for all fields are returned as the result, and recorded in its <code class="xref any docutils literal notranslate"><span class="pre">results</span></code>
< attribute. The value for each field is assigned as the <a class="reference internal" href="OutputPort.html#psyneulink.core.components.ports.outputport.OutputPort.value" title="psyneulink.core.components.ports.outputport.OutputPort.value"><code class="xref any py py-attr docutils literal notranslate"><span class="pre">value</span></code></a> of its <a class="reference internal" href="Composition.html#psyneulink.core.compositions.composition.NodeRole.OUTPUT" title="psyneulink.core.compositions.composition.NodeRole.OUTPUT"><code class="xref any py py-attr docutils literal notranslate"><span class="pre">OUTPUT</span></code></a>
< <a class="reference internal" href="Composition.html#composition-nodes"><span class="std std-ref">Nodes</span></a>. The input is then stored in its <a class="reference internal" href="#psyneulink.library.compositions.emcomposition.EMComposition.memory" title="psyneulink.library.compositions.emcomposition.EMComposition.memory"><code class="xref any py py-attr docutils literal notranslate"><span class="pre">memory</span></code></a>, with a probability
< determined by its <a class="reference internal" href="#psyneulink.library.compositions.emcomposition.EMComposition.storage_prob" title="psyneulink.library.compositions.emcomposition.EMComposition.storage_prob"><code class="xref any py py-attr docutils literal notranslate"><span class="pre">storage_prob</span></code></a> <a class="reference internal" href="Parameters.html#psyneulink.core.globals.parameters.Parameter" title="psyneulink.core.globals.parameters.Parameter"><code class="xref any py py-class docutils literal notranslate"><span class="pre">Parameter</span></code></a>, and all previous memories decayed by its
< <a class="reference internal" href="#psyneulink.library.compositions.emcomposition.EMComposition.memory_decay_rate" title="psyneulink.library.compositions.emcomposition.EMComposition.memory_decay_rate"><code class="xref any py py-attr docutils literal notranslate"><span class="pre">memory_decay_rate</span></code></a>. The <a class="reference internal" href="#psyneulink.library.compositions.emcomposition.EMComposition.memory" title="psyneulink.library.compositions.emcomposition.EMComposition.memory"><code class="xref any py py-attr docutils literal notranslate"><span class="pre">memory</span></code></a> can be accessed using its
< <a class="reference internal" href="#psyneulink.library.compositions.emcomposition.EMComposition.memory" title="psyneulink.library.compositions.emcomposition.EMComposition.memory"><code class="xref any py py-attr docutils literal notranslate"><span class="pre">memory</span></code></a> Parameter.</p>
---
> in the form of an <a class="reference internal" href="AutodiffCo
...

See CI logs for the full diff.

[dependabot]

Superseded by #524.